Abstract

The study presents an adaptive neural network output feedback tracking control scheme for a class of complicated agricultural mechanical systems. The scheme includes a dynamic gain observer to estimate the un-measurable states of the system. The main advantages of the authors scheme are that by introducing non-separation principle design neural network controller and the observer gain are simultaneously tuned according to output tracking error, the semi-globally ultimately bounded of output tracking error and all the states in the closed-loop system can be achieved by Lyapunov approach. With the universal approximation property of NN and the simultaneous parametrisation, no Lipschitz assumption and SPR condition are employed which makes the system construct simple. Finally the simulation results are presented to demonstrate the efficiency of the control scheme.

Keywords:

Agricultural mechanical systems, higher relative degree, neural network, non-separation principle, output feedback,

References

1. Bullinger, E. and F. Allgower, 2005. Adaptive ?-tracking for nonlinear higher relative degree systems. Automatica, 41(7): 1191-2000.
   CrossRef    
2. Chen, W.S. and L.C. Jiao, 2010. Adaptive tracking for periodically time-delaying and nonlinearly parameterized system using multilayer neural networks. IEEE T. Neural Networ., 21(2): 345-351.
   CrossRef    PMid:20071256    
3. Chen, B., X.P. Liu, K.F. Liu and C. Lin, 2009. Direct adaptive fuzzy control of nonlinear strict-feedback systems. Automatica, 45(6): 1530-1535.
   CrossRef    
4. Du, H. and S.S. Ge, 2010. Output feedback adaptive neural control for a class of non-affine nonlinear systems with a dynamic gain observer. IET Control Theory A., 5(3): 486-497.
   CrossRef    
5. Ge, S.S. and J. Zhang, 2003. Neural-network control of nonaffine nonlinear system with zero dynamics by state and output feedback. IEEE T. Neural Networ., 14: 900-918.
   CrossRef    PMid:18238069    
6. Hu, H., G.R. Liu, H.Z. Tang and P. Guo, 2010a. Robust output tracking control for mismatched uncertainties nonlinear systems. Nat. Sci. J. Xiangtan Univ., 32(4): 108-111.
   
7. Hu, H., G.R. Liu, D.B. Liu and P. Guo, 2010b. Output feedback tracking control for a class of uncertain nonlinear MIMO systems using neural network. Control Theor. Appl., 27(8): 382-386.
   
8. Leu, Y.G., W.Y. Wang and T.T. Lee, 2005. Observer-based direct adaptive fuzzy-neural control for nonaffine nonlinear systems. IEEE T. Neural Networ., 16(4): 853-861.
   CrossRef    PMid:16121727    
9. Liu, G.R. and B.W. Wan, 2002. Direct adaptive fuzy robust control for a class of nonlinear MIMO systems. Control Theor. Appl., 19(5): 693-698.
   
10. Liu, Y.J., W. Wang and S.C. Tong, 2010. Robust adaptive tracking control for nonlinear systems based on bounds of fuzzy approximation parameters. IEEE T. Syst. Man Cy. A, 40(1): 170-184.
    CrossRef    
11. Qian, C. and W. Liu, 2002. Output feedback control of a class of nonlinear systems: A non-separation principle paradigm. IEEE T. Automat. Contr., 47(10): 1710-1715.
    CrossRef    
12. Tong, S.C. and L.J. Qu, 2005. Fuzzy adaptive output feedback control for a class of MIMO nonlinear systems. Control Decision, 27: 781-793.
    
13. Wang, Y.F., T.Y. Chai and Y.M. Zhang, 2010. State observer-based adaptive fuzzy output feedback control for a class of uncertain nonlinear systems. Inform. Sciences, 180: 5029-5040.
    CrossRef    
14. Yu, J.P., Y.M. Ma, B. Chen and H.S. Yu, 2011. Adaptive fuzzy backstepping position tracking control for a permanent magnet synchronous motor. Int. J. Innov. Comput. I., 7(4): 1589-1602.
    

Competing interests

The authors have no competing interests.

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